Hi Sven,
just use:
lm(y~(x1+x2+x3+...+x10)^10)
e.g.,
y <- rnorm(5000) x1 <- factor(sample(0:1, 5000, TRUE)) x2 <- factor(sample(0:1, 5000, TRUE)) x3 <- factor(sample(0:1, 5000, TRUE)) x4 <- factor(sample(0:1, 5000, TRUE))
lm1 <- lm(y~(x1+x2+x3+x4)^4) summary(lm1)
I hope it helps.
Best, Dimitris
---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.ac.be/biostat http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
----- Original Message ----- From: "Sven" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Tuesday, November 30, 2004 12:59 PM
Subject: [R] 2k-factorial design with 10 parameters
Hi,
I'd like to apply a 2^k factorial design with k=10 parameters. Obviously this results in a quite long term for the model equation due to the high number of combinations of parameters.
How can I specify the equation for the linear model (lm) without writing all combinations explicitly down by hand? Does a R command exist for this problematic?
Thanks for your help in advance, Sven
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